A polynomial time algorithm for optimizing join queries

The dynamic programming algorithm for query optimization has exponential complexity. An alternative polynomial time algorithm, the IK-KBZ algorithm, is severely limited in the queries it can optimize. Other algorithms have been proposed, including the greedy algorithm, iterative improvement, and sim...

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Bibliographic Details
Published inProceedings of IEEE 9th International Conference on Data Engineering pp. 345 - 354
Main Authors Swami, A.N., Iyer, B.R.
Format Conference Proceeding
LanguageEnglish
Published IEEE Comput. Soc. Press 1993
Subjects
Annealing
Costs
Dynamic programming
Explosions
Greedy algorithms
Heuristic algorithms
Iterative algorithms
Polynomials
Prototypes
Query processing
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Summary:The dynamic programming algorithm for query optimization has exponential complexity. An alternative polynomial time algorithm, the IK-KBZ algorithm, is severely limited in the queries it can optimize. Other algorithms have been proposed, including the greedy algorithm, iterative improvement, and simulated annealing. The AB algorithm, which combines randomization and neighborhood search with the IK-KBZ algorithm, is presented. The AB algorithm is much more generally applicable than IK-KBZ, has polynomial time and space complexity, and produces near optimal plans in the space of outer linear join trees. On average, it does better than the other algorithms that do not do an exhaustive search like dynamic programming.< >
ISBN:0818635703
9780818635700
DOI:10.1109/ICDE.1993.344047